Human Papillomavirus (HPV), a DNA virus, belongs to the Papillomaviridae family and the Papillomavirus genus, and mainly infects human epidermis and mucosa tissues. About 170 types of HPV have been identified, wherein some types cause warts and cancers after invading the human body, but others do not cause any symptoms. Some research indicates that 99.7% of cervical cancer is caused by HPV infection.
According to a report from the World Health Organization (WHO), cervical cancer is the second most common cancer in women in the world. According to statistics from the Ministry of Health and Welfare, the Executive Yuan, Taiwan, the annual incidence rate of cervical cancer in Taiwan is 27 cases per 100,000 women, and the age-standardized mortality rate of cervical cancer is 9.18 persons per 100,000 cases. More than 1,000 women on average die from cervical cancer per year; that is, 3 women die from cervical cancer per day. Therefore, there needs to be pathology detection for cervical cancer to determine whether pathological variations occur in the cervical cancer cells.
Pathology detection worldwide was valued at about US$1.98 billion in 2012, and will increase to US$5.7 billion in 2020, indicating that the compound growth rate is as much as14.3%. The compound growth rate in the Asia-Pacific market, which leapt to the highest in the world, is 22.2%, and the Asia-Pacific area has become the area with the most market potential for development. The compound growth rate in North America and Europe is 79%, and North America and Europe are the most common areas which use digital pathology detection and identification. The global pathology detection market is classified into Whole Slide Imaging (WSI), Image Analysis-Informatics & Storage, and Communication and Integrated Platforms, wherein WSI has the largest market demand. Thus, the growth of global pathology screening and diagnostic systems is faster than expected. Because the specimens for the pathology screening were entirely analyzed and observed one by one by medical technicians in the past and the speed cannot keep up with the increasing growth rate and the increasing number of Pap smears, a system that would benefit pathologists to analyze and identify pathology detection and fully satisfy clinical needs and market expectations, and would solve the technician shortage and overstrain problems for doctors and pathologists.
In general, malignant cervical cancer cells may deform, whereas the cell nucleus becomes larger, and thus cellular characteristic parameters may be analyzed to determine whether the cervical cells are malignant. The cellular characteristic parameters include the cell nuclear-cytoplasmic radius ratio, cell nuclear-cytoplasmic area ratio, cell nuclear morphology, cell membrane morphology and cell density in stain, etc. For example, the cell nucleus of a malignant cell becomes larger causing its cell nuclear-cytoplasmic radius (or area) ratio to be larger than that of a normal cell, and thus a cell where its nuclear-cytoplasmic ratio has become larger is determined to be a malignant cell. The current pathology screening system is a method where an image of cervical cells is segmented, the cellular characteristics are calculated and the malignancy of the cells is classified. However, a great deal of noise exists in the images of the actual Pap smears, where the size and the color of inflamed cells are the most similar to those of the cell nucleus of the cervical cells, and it is easy to mistake these inflamed cells as the cell nucleus of the cervical cells when retrieving the outline of the nucleus. Furthermore, this process leads to errors in the cellular segmentation and characteristics calculation, and causes irregular determination results after the cellular malignancy classification. For instance, as shown in FIG. 1(a), there are no inflamed cells in an ideal image of the cellular specimen, and the cell nucleus of the cervical cell can be clearly identified. However, there must be some inflamed cells in the female's ostium vagina. The inflamed cells neighboring the female's ostium vagina together with the cervical cells are sampled during the Pap smear sampling. The image characteristics of these inflamed cells are highly similar to those of the cell nucleus of the cervical cell, and these inflamed cells are either outside of the cytoplasm of the cervical cell (as shown in FIG. 1(b)) or inside the cytoplasm of the cervical cell (as shown in FIG. 1(c)). Therefore, to a digital image software identification system, it is easy to misidentify the inflamed cells dispersed inside the cytoplasm of the cervical cell as the cell nucleus of the cervical cell. In addition, if the inflamed cells are not excluded, the system may define all inflamed cells as a cell nucleus to analyze the cellular characteristic parameters (such as the nuclear-cytoplasmic ratio). Subsequently, the system may calculate areas or radiuses of all inflamed cells to enlarge the nuclear-cytoplasmic ratio and misjudge the cells as malignant cells or abnormal cells when calculating the nuclear-cytoplasmic ratio. Accordingly, to avoid this misjudgment, the system needs to exclude the noise (such as a disturbance from the inflamed cells) in the cell image, to increase the accuracy of the system during the cervical cell screening.
To overcome the disadvantages above, it is ideal to have a new digital pathologic screening and diagnostic device and method. It is therefore the Applicant's attempt to deal with the many limitations in the prior art.